Module 4 / Lesson 10.2
Moore's Law
Moore's Law
Learning:
- Read the text description to understand Moore's law
- Watch the embedded video to understand why it is considered a law.
Reflection: As you watch, focus on
- Why Moore’s Law is considered an industry trend, not a physical law.
- How exponential growth differs from linear growth.
- Examples from your own experience where technology got both cheaper and more powerful (phones, laptops, storage).
Moore’s Law was first observed by Gordon Moore, co-founder of Intel, in 1965. It is the idea that the number of transistors on a computer chip doubles roughly every two years. This trend has driven exponential increases in computing power while costs fell, fueling rapid progress in technology and artificial intelligence. Understanding Moore’s Law is essential to explaining why AI research has accelerated so dramatically: with more powerful and cheaper hardware, researchers can train larger models and push AI beyond what was once thought possible. This relentless improvement means that computers are not only getting faster, but fundamentally better in their application, For example:
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The shrinking size and cost of transistors allow powerful computing capabilities to be embedded in everyday objects, driving the rise of the Internet of Things (IoT) and highly capable portable devices like modern smartphones.
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The economic viability of packing billions of transistors onto a single chip has led to the development of specialized processors, like GPUs and TPUs, which are essential for the massive parallel computations required by modern AI.
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Unprecedented computing power allows scientists and engineers to run incredibly sophisticated models, accelerating progress in fields like climate change modeling, new drug discovery, and nuclear fusion research.
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As the performance-to-price ratio improves, access to high-end computing resources becomes cheaper (often through cloud services), lowering the barrier to entry for startups and researchers worldwide.
Ultimately, this continual doubling of processing power and efficiency is the engine behind the ongoing digital revolution, making tomorrow's technologies possible today.